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Proceedings Paper

Heterogeneous CPU-GPU moving targets detection for UAV video
Author(s): Maowen Li; Linbo Tang; Yuqi Han; Chunlei Yu; Chao Zhang; Huiquan Fu
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Paper Abstract

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104203R (21 July 2017); doi: 10.1117/12.2281531
Show Author Affiliations
Maowen Li, Beijing Institute of Technology (China)
Linbo Tang, Beijing Institute of Technology (China)
Yuqi Han, Beijing Institute of Technology (China)
Chunlei Yu, Beijing Institute of Technology (China)
Chao Zhang, Beijing Institute of Technology (China)
Huiquan Fu, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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